Bearings may be used with various types of rotating machinery in order to provide for relatively smooth rotation. For example, bearings may support a shaft of an electric machine, such as a motor or generator, such that the shaft may deliver power from or to the electric machine. Bearings may also support rotating components, including other shafts, in various other applications.
Generally, bearings tend to wear during use, such that one or more parts of the bearing may eventually fail. Depending on the character of use and wear, various parts of a bearing may be subject to failure, including inner and outer races, rolling elements (e.g., balls or rollers), a bearing cage.
Unexpected failure of a bearing may prevent continuing operation of the affected device. For example, where a bearing of an electric machine fails, the electric machine may be rendered inoperable until a replacement bearing has been installed. As such, unexpected failure of bearings may lead to unexpected downtime for maintenance. Various methods are known for predicting bearing failure, such as measurement of overall vibration levels of a bearing housing, or comparison of peak vibrations with average vibrations. These methods may exhibit various deficiencies, however, including failure to detect faults sufficiently in advance of failure, failure to detect certain types of faults, failure to distinguish potential bearing failures from other system effects, and the need to install sensors (e.g., vibration sensors) that are not otherwise needed for control of the relevant system. Accordingly, it may be useful to provide a system for improved identification of expected bearing failure in advance of actual failure of a bearing.